U.S. DEPARTMENT OF EDUCATION

Impacts of Comprehensive 

Teacher Induction

Results From the First Year of a Randomized Controlled Study

Executive Summary

NCEE 2009-4035
Impacts of Comprehensive 

Teacher Induction

Results From the First Year of a Randomized Controlled Study

Executive Summary

OCTOBER 2008

Steven Glazerman

Sarah Dolfin

Martha Bleeker

Amy Johnson

Eric Isenberg

Julieta Lugo-Gil

Mary Grider

Mathematica Policy Research, Inc.

Edward Britton

WestEd

Melanie Ali

Project Officer

Institute of Education Sciences

NCEE 2009-4035

U.S. DEPARTMENT OF EDUCATION
U.S. Department of Education

Margaret Spellings

Secretary

Institute of Education Sciences

Grover J. Whitehurst

Director

National Center for Education Evaluation and Regional Assistance

Phoebe Cottingham

Commissioner

October 2008

The report was prepared for the Institute of Education Sciences under Contract No. ED-04-CO-0112/001. The project 

officer is Melanie Ali in the National Center for Education Evaluation and Regional Assistance.

IES evaluation reports present objective information on the conditions of implementation and impacts of the programs 

being evaluated. IES evaluation reports do not include conclusions or recommendations or views with regard to actions 

policymakers or practitioners should take in light of the findings in the reports.

This report is in the public domain. Authorization to reproduce it in whole or in part is granted. While permission to reprint 

this publication is not necessary, the citation should be: Steven Glazerman, Sarah Dolfin, Martha Bleeker, Amy Johnson, Eric 

Isenberg, Julieta Lugo-Gil, Mary Grider, and Edward Britton (2008). Impacts of Comprehensive Teacher Induction: Results From the 

First Year of a Randomized Controlled Study — Executive Summary (NCEE 2009-4035). Washington, DC: National Center for 

Education Evaluation and Regional Assistance, Institute of Education Sciences, U.S. Department of Education.

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A CKNOWLEDGMENTS

his study was the product of many people’s efforts beyond the authors of this report. 

The technical working group for the study provided useful insight into and reactions 

to earlier presentations of methods and findings. The group included Carol Bartell, 

Mark Berends, Larry Hedges, Hamilton Lankford, Rebecca Maynard, Sandra Odell, Jeffrey 

Smith, and Todd Stinebrickner. We wish we could name the many dedicated individuals in 

the 17 participating school districts who provided us with data and cooperated with the 

study in many ways. These people were extraordinarily generous with their time and 

expertise. 

T

At WestEd, Cathy Ringstaff did an excellent job coordinating the field visits and other 

work needed to monitor implementation of the induction programs. Staff from the two 

induction programs—Educational Testing Service and the New Teacher Center at the 

University of California, Santa Cruz—were extremely cooperative with study demands and 

generously shared all facets of their programs with us. 

At Mathematica, Pat Nemeth oversaw a complex multi-wave data collection effort as 

the survey director, ably assisted by Linda Mendenko and Nakis Evgeniou. Amy Raduzycki, 

Phyllis Schulman, and Susan Golden played critical roles in achieving high response rates to 

the surveys. Renée Nogales was instrumental and very persistent in gathering test score 

records from the many districts that participated in the study. Gail Baxter, Kristin Hallgren, 

and Kathy Sonnenfeld coordinated with districts at several stages. Matthew Jacobus and 

Ama Takyi-Laryea, assisted by Dominic Harris and Elizabeth Seif, provided expert 

programming assistance. Roberto Agodini carefully reviewed drafts of the report and 

provided helpful comments. The report was produced by Donna Dorsey. Mustafa Menai 

and Mindy Hu provided additional production support. 

This study incorporates data on individual teachers’ college entrance examination scores 

provided to Mathematica by the College Board and by ACT. 

D ISCLOSURE OF P OTENTIAL C ONFLICTS 

OF I NTEREST T

 

1

he research team for this evaluation consists of a prime contractor, Mathematica 

Policy Research, Inc., of Princeton, NJ, and one subcontractor, WestEd of San 

Francisco, CA. Neither of these organizations nor their key staff members have 

financial interests that could be affected by findings from the evaluation of the two 

comprehensive teacher induction programs considered in this report. No one on the 

Technical Working Group, convened by the research team to provide advice and guidance, 

has financial interests that could be affected by findings from the evaluation. 

T

1 Contractors carrying out research and evaluation projects for IES frequently need to obtain expert 

advice and technical assistance from individuals and entities whose other professional work may not be entirely 

independent of or separable from the tasks they are carrying out for the IES contractor. Contractors endeavor 

not to put such individuals or entities in positions in which they could bias the analysis and reporting of results, 

and their potential conflicts of interest are disclosed. 

E XECUTIVE S UMMARY

ne of the main policy responses to the problems of turnover and inadequate 

preparation among beginning teachers is to support them with a formal, 

comprehensive induction program. Such a program might include a combination of 

school and district orientation sessions, special in-service training (professional 

development), mentoring by an experienced teacher, classroom observation, and formative 

assessment (Berry et al. 2002). 

O 

In practice, teacher induction is common, but induction that is intensive, 

comprehensive, structured, and sequentially delivered in response to teachers’ emerging 

pedagogical needs is less so (Berry et al. 2002; Smith and Ingersoll 2004). An example of 

informal or low intensity teacher induction includes pairing each new teacher with another 

full-time teacher without providing any training, supplemental materials, or release time for 

the induction to occur. 

There is little empirical evidence on whether investing more resources in a more 

comprehensive, and hence more expensive, induction program would help districts attract, 

develop, and retain beginning teachers. According to several research reviews (Ingersoll and 

Kralik 2004; Totterdell et al. 2004; Lopez et al. 2004), little of the research on teacher 

induction to date has been conclusive or rigorous. Research based on federal statistics (for 

example, Smith and Ingersoll 2004; Henke et al. 2000; Alt and Henke 2007) can provide a 

useful, nationally representative perspective on the issue, but it is limited to the extent it can 

capture the intensity of induction supports and in the range of outcomes that can be 

examined. Research at the local level (for example, Fuller 2003; Youngs 2002) has yielded 

more detailed descriptions of teacher supports. Like the national studies, however, it has 

relied on evaluation designs that leave doubt about whether the inferences are causal. 

Congressional interest in formal, comprehensive teacher induction has grown in recent 

years. The No Child Left Behind Act of 2001 (NCLB), which reauthorized the Elementary 

and Secondary Education Act of 1965 (ESEA), emphasizes the importance of teacher quality 

in student improvement. Title II, Part A of ESEA—the Improving Teacher Quality State 

Grants program—provides nearly $3 billion a year to states to train, recruit, and prepare high 

quality teachers. The implementation of teacher induction programs is one allowable use of 

these funds. Current discussions on the reauthorization of NCLB argue for a continued 

focus on supporting teachers through professional development opportunities and teacher 
viii 

Executive Summary 

mentoring programs, with a call to fund “proven models” to meet these objectives. In 

addition, the Higher Education Opportunity Act of 2008 authorizes grants that include 

teacher induction or mentoring programs for new teachers. These initiatives highlight the 

need to conduct rigorous research to determine whether comprehensive teacher induction 

programs produce a measurable impact on teacher retention and other positive outcomes for 

teachers and students. 

The National Center for Education Evaluation and Regional Assistance within the U.S. 

Department of Education’s (ED) Institute of Education Sciences (IES) contracted with 

Mathematica Policy Research, Inc. (MPR), to evaluate the impact of structured and intensive 

teacher induction programs. Throughout this report, we refer to the more formal, structured 

programs as “comprehensive” induction. The study examines whether comprehensive 

teacher induction programs lead to higher teacher retention rates and other positive teacher 

and student outcomes as compared to prevailing, generally less comprehensive approaches 

to supporting new teachers. More specifically, the study is designed to address five research 

questions on the impacts of teacher induction services: 

1. What is the effect of comprehensive teacher induction on the types and intensity 

of induction services teachers receive compared to the services they receive 

from the districts’ current induction programs? 

2. What are the impacts on teachers’ classroom practices? 

3. What are the impacts on student achievement? 

4. What are the impacts on teacher retention? 

5. What is the impact on the composition of the district’s teaching workforce? 

In 2004, we issued a Request for Proposals (RFP) to implement a comprehensive 

induction program as part of the study. The RFP specified that the induction program 

should include several components that earlier research and professional wisdom gleaned 

from practice had suggested were important features of successful teacher induction 

programs (Alliance for Excellent Education 2004; Ingersoll and Smith 2004; Smith and 

Ingersoll 2004; Kelly 2004; Serpell and Bozeman 2000). 

The components that constitute comprehensive teacher induction include the following: 

carefully selected and trained full-time mentors; a curriculum of intensive and structured 

support for beginning teachers that includes an orientation, professional development 

opportunities, and weekly meetings with mentors; a focus on instruction, with opportunities 

for novice teachers to observe experienced teachers; formative assessment tools that permit 

evaluation of practice on an ongoing basis and require observations and constructive 

feedback; and outreach to district and school-based administrators to educate them about 

program goals and to garner their systemic support for the program. 
 ix 

 Executive Summary 

A group of outside expert reviewers read and scored the proposals we received in 

response to the RFP. Among the proposals received, those submitted by Educational 

Testing Service of Princeton, New Jersey (ETS) and the New Teacher Center at the 

University of California-Santa Cruz (NTC) stood out as most closely meeting the study’s 

specified requirements. The two programs included the required components and were 

roughly comparable in structure. MPR therefore contracted with both providers to deliver 

one year of comprehensive induction services to the districts in the study, with one-half of 

the districts assigned to ETS, the remaining half to NTC. Researchers from WestEd, a 

subcontractor to MPR, monitored the implementation of the comprehensive induction 

services to help the providers ensure there was fidelity to the core service model and to 

identify and help address any implementation challenges that arose. 

STUDY DESIGN

The centerpiece of the study design is the use of random assignment to create a group 

of teachers exposed to comprehensive teacher induction (treatment) and an equivalent group 

exposed to the district’s usual set of induction services (control). The study design allows us 

to measure and compare outcomes for these two groups to estimate the impacts of 

comprehensive induction relative to the services teachers receive from their district’s 

prevailing induction program. As discussed below, we used surveys, classroom observations, 

and school records to measure the background of the study teachers, their receipt of 

induction services and alternative support services, their attitudes, and their outcomes related 

to the study’s main research questions: classroom practices, student achievement, and 

teacher mobility. 

We recruited 17 school districts to participate in the study. The districts, which were 

spread across 13 states, served low-income students, with every district in the study having 

more than 50 percent of its students qualifying for the federal School Lunch Program. We 

then assigned each district to one of the two providers of comprehensive induction, either 

ETS or NTC, based primarily on district preferences. The preference-based method of 

assigning districts to providers does not allow for and should not be used to make direct 

comparisons of one provider to the other. 

Within each district, a subset of elementary schools participated in the study. The study 

used an experimental design in which we randomly assigned elementary schools within each 

of the 17 participating districts to either a treatment group, which received comprehensive 

teacher induction—from ETS or NTC, depending on the district—or a control group, 

which took part in the district’s usual teacher induction program. Districts nominated 

approximately 500 schools across the 17 districts. It turned out that some schools that we 

targeted for random assignment had no eligible teachers, so the final sample sizes included 

418 schools: 100 treatment schools and 103 control schools in the 9 ETS districts and 110 

treatment and 105 control schools in the 8 NTC districts. 

With each study school, we selected all eligible teachers, defined as beginning teachers 

who met certain criteria: taught in an elementary grade (K-6); were new to the profession; 

and were not already receiving induction support from a teacher preparation or certification 

program. The 418 schools participating in the study contained 1,009 eligible teachers. 
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Executive Summary 

Not all of the 1,009 teachers eligible for the study were eligible for all analyses. We 

limited the collection of classroom practices data to 698 teachers who met certain eligibility 

requirements such as teaching English/language arts to a self-contained classroom. Because 

we focused on reading instruction, it was not appropriate or even possible to include 

teachers such as music, art, or math specialists who were not responsible for teaching 

reading. We limited the collection of student test score data to teachers meeting another set 

of eligibility criteria, including teaching a self-contained classroom in a tested grade and 

subject. This resulted in the collection of reading test scores for 281 teachers and math 

scores for 261 teachers. 

Eligible teachers in a school were either all exposed or all not exposed to treatment, a 

method known as cluster random assignment. Cluster random assignment was necessary 

because varying the types of induction services available in the same school building could 

result in contamination of the control group. Therefore, we assigned all eligible teachers to 

treatment or control status based on the school where they were expected to teach at the 

point of random assignment. 

We found that random assignment produced groups that were equivalent on a wide 

variety of teacher and school characteristics. Of the dozens of baseline attributes we 

examined, we found statistically significant differences between treatment and control 

groups in one area: teacher assignments.2

 The control group contained a higher percentage 

of special subject teachers (such as art and music) than did the treatment group (7 versus 3 

percent) and consequently a lower percentage of teachers who taught just a single grade (79 

versus 85 percent) and who said they were responsible for math (85 versus 90 percent) or 

reading outcomes (83 versus 91 percent). Accounting for such differences did not change 

the study’s conclusions. 

METHODS AND DATA

We used a model-based approach to estimate program impacts. The statistical model 

explicitly acknowledges the hierarchical structure of the data—for example, the nesting of 

teachers within schools—an approach that is sometimes referred to as a hierarchical linear 

model (HLM). Accordingly, we can properly specify the units of analysis (teachers and 

schools) and devise unbiased estimates of the standard errors that we used to conduct 

hypothesis tests. The model also allows us to control for the effects of a range of teacher and 

school characteristics on the outcomes of interest to increase the precision of the estimates 

of treatment effects. The set of benchmark control variables (covariates), which differs for 

each outcome, are described in the discussion of key study findings. 

To test the robustness of the study findings, we conducted several sensitivity tests. 

These tests included re-estimation of the study’s main impacts with different sets of 

covariates and sample weights and different statistical model assumptions. We also reported 

whether the findings would change if we were to use post-hoc adjustments for multiple 

 2 All differences discussed in the text are statistically significant at the 0.05 level unless stated otherwise. 
 xi 

 Executive Summary 

comparison errors. Multiple comparison errors are those that arise when researchers report 

on a large number of hypothesis tests, at least some of which may result in falsely rejecting 

the null hypothesis. Specifically, we applied a method developed by Benjamini and Hochberg 

(1995) for reducing the rate of false discoveries. 

Findings are pooled across ETS and NTC districts throughout this report because the 

study was intended to explore the effects of comprehensive teacher induction in general, not 

the specific impacts of any one program. However, we conducted separate analyses by 

district type (ETS or NTC) to ensure that the findings were not peculiar to one of the 

providers. 

Data for the study were collected from a variety of sources. We administered a baseline 

teacher survey in fall 2005, at which time we also requested teachers’ permission to obtain 

their college entrance examination scores (SAT or ACT). The baseline survey asked teachers 

about their formal education, professional training, current teaching assignment, and 

personal background. We surveyed teachers twice during the 2005-2006 school year on the 

induction activities in which they participated, including questions about duration and 

intensity of mentoring and professional development as well as questions about satisfaction 

with and preparedness for different aspects of their current teaching position. We surveyed 

mentors participating in the comprehensive induction programs on their background 

characteristics and reviewed program documents from ETS and NTC. Additional detail on 

these measures is included in the discussion of findings below. 

For the study’s core outcomes, we observed the teachers teaching a literacy unit in the 

classroom in the spring of 2006, collected districts’ student records data at the end of the 

2005-2006 school year, and conducted the first of three mobility surveys in fall 2006 to learn 

about teacher retention. We achieved response rates of over 85 percent on the teacher 

surveys and observations, although the rates for the control group (for example, 92 percent 

on the background survey) were not as high as those for the treatment group (97 percent on 

the same survey). We used nonresponse adjustment weights and sensitivity analyses to 

address the differential response rates. 

The instrument used to conduct the observations was the Vermont Classroom 

Observation Tool (VCOT). The VCOT measures the teacher practices that current research 

suggests are essential to good teaching or that have been linked to student achievement 

growth (Cawelti 2004). The VCOT also measures instructional practices that closely reflect 

those recognized by both the ETS and NTC induction programs, particularly for literacy 

instruction. We observed eligible study teachers once while they were teaching a literacy unit. 

The observations lasted between one to two hours, with duration dependent on how the 

district or school structured its class periods. Observers scored teachers in each of three 

constructs based on a set of items that are believed to be indicators of good practice: 

implementation of a lesson, content of a lesson, and classroom culture. Implementation was 

measured with five items that focused on the effectiveness of instruction and learning that 

occurred during the lesson. Content was measured with four items that assessed the 

accuracy, importance, level of abstraction, and connections to other concepts. Classroom 

culture was measured with seven items that assessed the learning environment, the level of 
xii 

Executive Summary 

student engagement, the nature of working relationships, and issues of student equity 

(Saginor and Hyjek 2005). The three domains comprise five, four, and seven items, 

respectively. Observers rated the extent of evidence of teacher behavior for each item on a 

five-point scale showing (1) no evidence, (2) limited evidence, (3) moderate evidence, (4) 

consistent evidence, or (5) extensive evidence. 

We measured student achievement outcomes using district-administered test score data 

from the spring 2006 (post-test) for students taught by study teachers in the 2005-2006 

school year and students’ linked scores from the prior grade in spring 2005 (pre-test).3 We 

conducted all treatment-control comparisons within grade and within district to ensure that 

treatment status was not confounded with properties of the test. 

THE TREATMENT: COMPREHENSIVE INDUCTION SERVICES

The comprehensive induction program components included carefully selected and 

trained full-time mentors; a curriculum of intensive and structured support for beginning 

teachers; a focus on instruction, with opportunities for novice teachers to observe 

experienced teachers; formative assessment tools that permit evaluation of practice on an 

ongoing basis and require observations and constructive feedback; and outreach to district 

and school-based administrators to educate them about program goals and to garner their 

systemic support for the program. The curriculum included a number of activities. Mentors 

were asked to meet weekly with treatment teachers for approximately two hours. 

Conversation was expected to center around the induction programs’ teacher learning 

activities, but mentors also exercised professional judgment in selecting additional activities 

to meet beginning teachers’ needs, including observing instruction or providing a 

demonstration lesson; reviewing lesson plans, instructional materials, or student work; or 

interacting with students. Treatment teachers were also provided monthly professional 

development sessions to complement their interactions with mentors, and the ETS districts 

also offered monthly study groups—mentor-facilitated peer support meetings for treatment 

teachers. Treatment teachers also observed veteran teachers once or twice during the year. 

At the end of the school year, treatment teachers in both ETS and NTC districts participated 

in a colloquium celebrating the year’s successes and teachers’ professional growth. 

The goal of the study was to assign each mentor to 12 beginning teachers, though 

mentor caseloads ranged from 8 to 14 teachers over the course of the year. The program 

providers sought individuals with a minimum of five years of teaching experience in 

elementary school, recognition as an exemplary teacher, and experience in providing 

professional development or mentoring other teachers (particularly beginning teachers). The 

providers brought their respective mentors together for 10 to 12 days of training. The 

training was spread across four sessions of 2 to 3 days, with the first session held during the 

summer of 2005 and the rest taking place throughout the school year. Trainings previewed 

the content of upcoming professional development sessions and gradually introduced 

processes of mentor/mentee work in such areas as reflecting on instructional practices and 

 3 One district tested students in the fall, so we used data that tracked growth from fall 2005 to fall 2006. 
 xiii 

 Executive Summary 

analyzing student work. The trainings focused on improving beginning teachers’ instruction, 

including the use of forms and processes to accomplish this, and mentoring skills for 

working with beginning teachers, such as using evidence from teachers’ instruction rather 

than presenting opinions, and conversational techniques such as paraphrasing and asking 

clarifying questions. Additional support and development opportunities were provided to 

mentors during the year through weekly meetings of district mentors as well as feedback and 

advice from district coordinators and program staff. 

Both the ETS and NTC programs are based on a curriculum expected to promote 

effective teaching. The ETS program defines effective teaching in terms of 22 components 

organized into four domains of professional practice.4 The components are aligned with the 

Interstate New Teacher Assessment and Support Consortium (INTASC 1992) principles. 

The NTC induction model defines effective teaching in terms of six Professional Teaching 

Standards. Each standard, or domain, is broken into a succession of more discretely defined 

categories of teaching behaviors.5

 

There are other similar features as well. Under each program, the mentor’s goal is to 

help beginning teachers use evidence from their own practice to recognize and implement 

effective instruction as defined by the domains or standards. Both induction programs use a 

continuum of performance as a means for teachers to establish a benchmark and improve 

their instructional practice. 

Practitioners and policymakers should be aware that the programs implemented in this 

study by ETS and NTC were not necessarily the same models that would be delivered 

outside the study context. First, for study purposes, we aimed for consistent implementation 

of each program, with a high level of fidelity to the program design and a quick response to 

any implementation issues. Second, the providers adapted their program for the study to 

ensure that the required components were included in a one-year curriculum. Finally, each 

provider organized off-site mentor training sessions, bringing together the mentors from all 

of the provider’s study districts. For district-wide implementation with a larger number of 

mentors, training typically occurs within the district, rather than off-site together with 

mentors from other districts. 

 4 The four domains are planning and preparation, classroom environment, instruction, and professional 

responsibilities. As an example, components of the instruction domain include communicating clearly and 

accurately and using questioning and discussion techniques. The full set of components in each domain is 

presented in Chapter IV. 

5 The six standards are planning instruction and designing learning experiences, creating/maintaining 

effective environments, understanding/organizing subject matter, development as a professional educator, 

engaging/supporting all students in learning, and assessing student learning. As an example, categories of 

teaching behaviors in the standard of engaging/supporting all students in learning include connecting prior 

knowledge, life experience, and interests with learning goals and promoting self-directed, reflective learning. 

The full set of teaching behaviors in each standard is presented in Chapter IV. 
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Executive Summary 

SUMMARY OF FINDINGS: POSITIVE IMPACTS ON INDUCTION SUPPORT RECEIVED

We found statistically significant differences between the treatment and control groups 

in the amount, types, and content of induction support teachers reported having received 

(see Chapter IV). This finding was similar in the fall and the spring of the intervention year. 

Estimates were computed using an ordinary least squares model with district and grade 

assignment fixed effects that accounted for clustering of teachers within schools; weights 

were applied to adjust for survey nonresponse and the study design. 

Treatment Teachers Reported Receiving More Mentoring Than Did Control 

Teachers. Treatment teachers were significantly more likely than control teachers to report 

having any mentor (94 versus 83 percent) and having more than one mentor (29 versus 17 

percent). The types of mentors also differed between treatment and control groups. 

Treatment teachers were significantly more likely than control teachers to report having a 

mentor assigned to them (93 versus 75 percent) and to report having a full-time mentor (74 

versus 13 percent).6

 Treatment teachers reported spending significantly more time working 

with their mentors than control teachers did during the most recent full week of teaching. 

Treatment teachers reported spending an average of 95 minutes per week in mentor 

meetings compared to 74 minutes for control teachers, with the 21-minute difference 

attributable entirely to differences in the duration of scheduled meetings. For a typical school 

year of 36 weeks, the treatment-control difference in the total hours of mentor contact time 

during the year is estimated to be 12.5 hours. 

Treatment Teachers Were More Likely Than Control Teachers to Report 

Participating in Specific Induction Activities. Treatment teachers reported spending 

significantly more time during the most recent full week of teaching being observed by their 

mentors (26 versus 11 minutes), observing mentors modeling lessons (11 versus 7 minutes), 

and meeting one-on-one with a mentor (34 versus 21 minutes) or meeting with mentors and 

other first-year teachers (27 versus 7 minutes) as compared to control teachers. During the 

most recent full week of teaching, treatment teachers were 15 to 26 percentage points more 

likely than control teachers to report having received mentors’ assistance in a variety of topic 

areas, with a difference of more than 20 percentage points in discussing instructional goals 

and how to achieve them (70 versus 44 percent), receiving suggestions to improve practice 

(74 versus 52 percent), and receiving guidance on assessing students (62 versus 40 percent). 

Examining a broader window of three months prior to the spring survey, treatment teachers 

were a significant 7 to 36 percentage points more likely than control teachers to receive each 

type of guidance the survey asked about, with a difference of 25 percentage points or more 

in reflecting on instructional practice (68 versus 33 percent); managing classroom activities, 

transitions, and routines (65 versus 40 percent); reviewing and assessing student work (55 

 6 Although all treatment teachers were assigned a full-time ETS or NTC mentor, not all treatment 

teachers reported this person as their mentor. In addition, not all treatment teachers reported having a mentor 

assigned to them (as opposed to being someone the teacher sought out) or reported having a full-time mentor 

who had been released from teaching. We discuss teacher-reported mentor profiles in detail in Chapter IV. 
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 Executive Summary 

versus 30 percent); and using student assessments to inform their teaching (54 versus 29 

percent). 

Treatment Teachers Spent More Time in Certain Professional Activities Than 

Did Control Teachers During the Three Months Prior to the Spring Survey. During 

the three months prior to the spring survey, treatment teachers were significantly more likely 

than control teachers to report having kept written logs (40 versus 28 percent), worked with 

study groups of new teachers (68 versus 27 percent) and study groups of new and 

experienced teachers (47 versus 37 percent), and observed others teaching both in their 

classrooms (70 versus 42 percent) and in the teacher’s classroom (47 versus 38 percent). 

However, treatment and control teachers did not differ significantly in their likelihood to 

report having engaged in other activities such as keeping a portfolio and analysis of student 

work or meeting with principals, literacy or mathematics coaches, or resource specialists. 

Compared to control teachers, treatment teachers were significantly more frequently 

observed by mentors (3.4 versus 1.5 times), though not by principals, and more frequently 

given feedback on teaching both as part of a formal evaluation (1.7 versus 1.5 times) and not 

as part of a formal evaluation (2.5 versus 2.0 times) than control teachers during this period. 

Of 17 areas of professional development asked about, treatment teachers were significantly 

more likely than control teachers to report having attended professional development in 

three areas: lesson planning (38 versus 26 percent), analyzing student work/assessment (56 

versus 42 percent) and differentiated instruction (55 versus 46 percent). Treatment teachers 

reported spending significantly more time in professional development in 4 of the 17 areas: 

analyzing student work/assessment (58 versus 41 minutes), lesson planning (36 versus 26 

minutes), parent and community relations (23 versus 15 minutes), and assigning 

grades/record keeping (17 minutes versus 10 minutes). Treatment teachers reported 

spending significantly less time than control teachers in one area: preparing students for 

standardized testing (43 minutes versus 53 minutes). 

SUMMARY OF FINDINGS: NO IMPACTS ON TEACHER PRACTICES IN THE FIRST YEAR

Observers scored teachers on a set of 16 indicators of teaching practice using a fivepoint scale.7

 The indicators are grouped into three domains: lesson implementation, lesson 

content, and classroom culture. The analysis included teacher demographic characteristics, 

teacher’s educational and professional background, teaching assignment, school 

characteristics, and district and grade fixed effects. 

We observed no statistically significant differences between treatment and control 

teachers’ performance on any of the three domains of classroom practices (Table 1). We 

express the impact on each domain of classroom practice as the difference in scores on the 

five-point scale. An impact of 0.5 point, for example, would suggest that the intervention 

moves the average teacher from being able to demonstrate “moderate” evidence of good 

practice in that domain half of the distance to being able to demonstrate “consistent” 

evidence of good practice if they start at the moderate level. 

 7 The instrument used to conduct teacher observations was the Vermont Classroom Observation Tool 

(Saginor and Hyjek 2005). 
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Executive Summary 

Table 1. Impacts on Classroom Practices (Average Score on a 5-Point Scale) 

Outcome Treatment Control Difference 

Effect 

Size P-value 

Implementation of literacy lesson 2.7 2.6 0.0 0.02 0.766 

Content of literacy lesson 2.4 2.4 0.0 -0.01 0.875 

Classroom culture 3.1 3.0 0.0 0.04 0.629 

Unweighted Sample Size 

(Teachers) 

342 289 

Source: MPR classroom observations conducted in spring 2006; MPR Teacher Background Survey 

administered in 2005-2006 to all study teachers. 

Notes: Data are weighted and regression-adjusted using ordinary least squares to account for 

differences in baseline characteristics and the study design. Scoring scale: (1) no evidence, (2) 

limited evidence, (3) moderate evidence, (4) consistent evidence, or (5) extensive evidence of 

effective teaching practice. 

None of the differences is statistically significant at the 0.05 level, two-tailed test. 

SUMMARY OF FINDINGS: NO POSITIVE IMPACTS ON STUDENT TEST SCORES IN THE 

FIRST YEAR

The test score analysis was based on standardized achievement tests that the district 

normally conducts.8 While district-administered test scores may not cover every domain of 

student achievement that induction might affect, they do capture the content that school 

districts or states deem most important and worthy of assessing. We aggregated test scores 

across districts and grades by standardizing each test to a common metric called a z-score, 

which has a mean of zero and a standard deviation of one. The impact estimates are 

regression-adjusted using covariates that include the normalized student pre-test score, 

student characteristics, teacher personal characteristics, teacher professional characteristics, 

and district-by-grade fixed effects. 

The findings, summarized in Tables 2 and 3, show the grade-specific impact estimates 

to be negative and statistically significant for grade 2 for reading (effect size = -0.22) and for 

grades 2 and 3 for math (effect size = -0.38 and -0.26, respectively), but the average impacts 

across all grades were not significantly different from zero for math or reading. The findings 

were robust to different analysis methods, such as regression with an omitted pre-test or 

regression with alternative weights or different sets of control variables. 

 8 The specific test differs from district to district, and in some cases by grade within district. However, all 

treatment-control comparisons were made using a common set of tests (within grade within district). We 

standardized all test scores to have a mean of zero and a standard deviation of one to facilitate aggregation of 

impacts across districts and grades. 
 xvii 

 Executive Summary 

Table 2. Impacts on Reading Test Scores 

Adjusted Mean Test 

Scores Unweighted Student Sample Sizes 

Grade Treatment Control Difference 

Effect 

Size P-value Total 

Treatment 

Group 

Control 

Group 

2 -0.12 0.10 -0.22* -0.22 0.034 543 243 300 

3 -0.06 0.07 -0.13 -0.13 0.119 1,113 629 484 

4 0.02 -0.02 0.04 0.04 0.421 1,679 919 760 

5 0.01 -0.01 0.01 0.01 0.843 1,516 707 809 

6 -- -- -- -- 48 24 24 

All Grades 0.01 -0.01 0.01 0.01 0.735 4,899 2,522 2,377 

Source: MPR analysis of data from 2004-2005 and 2005-2006 provided by participating school districts;

MPR Teacher Background Survey administered in 2005-2006 to all study teachers. 

Notes: Data are regression-adjusted using a least squares model to account for baseline characteristics 

and clustering of students within schools. 

 

-- Impacts cannot be estimated due to treatment status being confounded with covariates. 

None of the differences is significantly different from zero after applying a Benjamini-Hochberg correction. 

*Significantly different from zero at the 0.05 level, two-tailed test.

SUMMARY OF FINDINGS: NO IMPACTS ON TEACHER RETENTION AFTER ONE YEAR

We found that comprehensive teacher induction had no statistically significant impact 

on teacher retention. We measured teacher retention in terms of the percentage of teachers 

who remained in their originally assigned school, their district, and the teaching profession. 

Table 4 shows the percentages of treatment and control teachers who stayed in the same 

school, moved within the profession, and left the teaching profession. The difference in 

mobility patterns between the two groups was not statistically significant. Even when we 

collapsed the mobility patterns into summary measures, we found no statistically significant 

differences between the treatment and control groups. 
xviii 

Executive Summary 

Table 3. Impacts on Math Test Scores 

Adjusted Mean Test 

Scores Unweighted Student Sample Sizes

Grade Treatment Control Difference 

Effect 

Size P-value Total 

Treatment 

Group 

Control 

Group 

2 -0.20 0.18 -0.38*† -0.38 0.000 472 226 246 

3 -0.11 0.15 -0.26*† -0.26 0.002 837 469 368 

4 0.01 -0.01 0.03 0.03 0.617 1,545 805 740 

5 -0.02 0.02 -0.04 -0.04 0.549 1,510 699 811 

6 -- -- -- -- 48 24 24 

All Grades -0.03 0.03 -0.05 -0.05 0.184 4,412 2,223 2,189 

Source: MPR analysis of data from 2004-2005 and 2005-2006 provided by participating school districts;

MPR Teacher Background Survey administered in 2005-2006 to all study teachers. 

Notes: Data are regression-adjusted using a least squares model to account for baseline characteristics 

and clustering of students within schools. 

 

-- Impacts cannot be estimated due to treatment status being confounded with covariates. 

*Significantly different from zero at the 0.05 level, two-tailed test. 

†

Significantly different from zero at the 0.05 level, two-tailed test, after applying a Benjamini-Hochberg 

correction. 

Table 4. Impacts on Teacher Mobility, by Destination (Percentages) 

Outcome Treatment Control Difference 

Stayers 

Stayed at original school 75.0 74.6 0.3 

Movers 

Moved, same district 11.2 10.6 0.6 

Moved, different district 6.3 7.4 -1.1 

Moved, private, parochial, or other school 2.4 1.4 1.1 

Leavers 

Left, to stay at home 0.8 1.3 -0.5 

Left, in school or new job 3.9 4.2 -0.3 

Left, other 0.4 0.5 -0.1 

Unweighted Sample Size (Teachers) 470 433 903 

Unweighted Sample Size (Schools) 201 193 394 

Source: MPR Mobility Survey administered in 2006-2007 and Teacher Background Survey administered 

in 2005-2006 to all study teachers. 

Note: Data are weighted to account for the study design. 

 Difference in the distributions is not statistically significant using a design-based F-test (p= 0.890). 
 xix 

 Executive Summary 

We also examined the reasons that teachers who left their districts (movers) or left the 

teaching profession (leavers) gave for leaving and found no statistically significant impacts of 

treatment. When we asked leavers whether they expected to return and if so, when they 

would do so, we did not find evidence of a treatment-control difference. In addition, we 

found that treatment teachers did not report feeling more satisfied with or better prepared 

for their jobs as teachers than control teachers. We will repeat these analyses in the coming 

years when we collect additional follow-up data, at which point we expect there to be more 

teacher mobility to explain. 

SUMMARY OF FINDINGS: NO POSITIVE IMPACTS ON COMPOSITION OF THE DISTRICT 

TEACHING WORKFORCE AFTER ONE YEAR

The last major research question concerned the impact of comprehensive teacher 

induction on the composition of the teaching workforce in the district. For comprehensive 

teacher induction to affect the composition of the district’s teaching workforce, it has to 

produce a difference in the types of teachers who decide to return to the district. As teachers 

leave the district, the average qualifications of the teachers who remain in the district begin 

to change, perhaps differentially between the treatment and control groups. We tested this 

hypothesis by comparing the characteristics of district stayers between the treatment and 

control groups along three dimensions: (1) their observed classroom practices; (2) their 

effect on student achievement; and (3) their professional characteristics such as SAT/ACT 

scores and advanced degrees. Classroom practice and student achievement outcomes are 

regression-adjusted using the same sets of covariates used in the main analysis. 

We found that the treatment had no positive impacts on the classroom practices, no 

positive impacts on student achievement (and one statistically significant negative impact), 

and no significant impacts on the professional background characteristics. Table 5 presents 

the impacts on classroom practices and student achievement outcomes for district stayers. 

Table 6 shows the background characteristics of teachers by mobility status. 

Correlational Analyses Explore Relationships between Induction and Outcomes 

Because a majority of both treatment and control teachers reported receiving induction 

support (93 percent of treatment teachers and 75 percent of control teachers reported 

having an assigned mentor), we looked at the relationship between the types and intensity of 

support and our three main outcome measures: classroom practices, student achievement, 

and teacher retention. These nonexperimental analyses investigate whether there was a 

relationship between induction support and outcomes, regardless of treatment status. The 

analyses mimic the experimental analyses discussed above, using the same covariates and 

model specification, but replacing the indicator for assignment to treatment status with a 

measure of induction services. We re-ran the model once for each of 12 measures of 
xx 

Executive Summary 

Table 5. Impacts on Classroom Practices and Student Achievement, District Stayers 

Only 

Outcome Treatment Control Difference Effect Size P-value 

Classroom Practices (Average Score on a 5-Point Scale) 

Implementation of literacy lesson 2.7 2.7 0.0 0.02 0.814 

Content of literacy lesson 2.4 2.4 0.0 -0.05 0.586 

Classroom culture 3.1 3.1 0.0 0.05 0.613 

Unweighted Sample Size (Teachers) 281 236 517 

Unweighted Sample Size (Schools) 153 141 294 

Student Achievement (Effect Size) 

Reading scores (all grades) 0.00 0.01 -0.01 -0.01 0.785 

Unweighted Sample Size (Students) 2,100 1,750 3,850 

Unweighted Sample Size (Teachers) 122 99 221 

Unweighted Sample Size (Schools) 94 73 167 

Math scores (all grades) -0.04 0.04 -0.08* -0.08 0.037 

Unweighted Sample Size (Students) 1,874 1,647 3,521 

Unweighted Sample Size (Teachers) 113 95 208 

Unweighted Sample Size (Schools) 87 70 157 

Source: MPR classroom observations conducted in spring 2006; MPR analysis of data from 2004-2005 

and 2005-2006 provided by participating school districts; MPR Teacher Background Survey 

administered in 2005-2006 and Mobility Survey administered in 2006-2007 to all study teachers. 

Note: Classroom practice means are weighted and regression-adjusted using ordinary least squares to 

account for differences in baseline characteristics and the study design. Student achievement 

means are regression-adjusted using a least squares model to account for baseline 

characteristics and clustering of students within schools. The test scores are expressed as zscores, with mean of 0 and standard deviation of 1 within each district and grade. 

*Significantly different from zero at the 0.05 level, two-tailed test. 
 xxi 

 Executive Summary 

induction services measured from the fall survey and again using the measures from the 

spring survey.9 The results from these analyses should be viewed cautiously. They should be 

used to generate hypotheses rather than to establish causal inferences because any 

association may confound effects of the induction services themselves with the pre-existing 

differences between the types of teachers who receive different levels of services. For 

example, those who receive the most support may be the most assertive and effective 

teachers who are most attached to the profession. Due to the number of analyses conducted, 

we focus upon the relationships that are statistically significant after applying a BenjaminiHochberg correction for multiple hypothesis testing within each of the three main outcome 

domains. 

After adjusting for multiple hypothesis testing, none of the relationships between the 

induction variables and classroom practices was statistically significant. Three of the 

relationships between the induction variables and student test scores and eight of the 

relationships between the induction variables and retention measures were positive and 

statistically significant. Specifically, students of teachers who reported meeting with a subject 

coach in the fall scored higher on math tests by 0.14 of a standard deviation. The students of 

teachers who reported receiving feedback on teaching during the fall scored higher on both 

math and reading tests by 0.02 of a standard deviation per instance that the teacher received 

feedback. Having an assigned mentor in the spring, receiving guidance in math or literacy 

content in the spring, each hour spent in the fall on professional development related to 

content area knowledge, and each hour spent in the fall and spring on professional 

development related to instructional techniques were associated with a 1 to 6 percentage 

point increase in the likelihood of remaining in the district or in the teaching profession. 

FUTURE RESEARCH

This report focused on the first year of findings only. The research team is conducting 

longer term followup to include additional collection of test score and teacher mobility data. 

In addition, the intervention was expanded to include a second year of services for treatment 

teachers in seven of the districts (4 ETS and 3 NTC), selected based on districts’ willingness 

and ability to continue the program. Future reports will therefore provide evidence on the 

longer-term effects of both a one-year program in 10 districts and a two-year program in 7 

districts. 

 9 The twelve induction measures were: whether the beginning teacher was assigned a mentor (yes/no), 

whether the beginning teacher met with a literacy or math coach (yes/no), whether the beginning teacher 

worked with a study group (yes/no), whether the beginning teacher observed others teaching (yes/no), whether 

the mentor gave the beginning teacher suggestions to improve his/her practices (yes/no), whether the 

beginning teacher received a “moderate amount” or “a lot” of guidance in math content (yes/no), whether the 

beginning teacher received a “moderate amount” or “a lot” of guidance in literacy content (yes/no), the 

frequency with which the beginning teacher received feedback on his/her teaching (number of times in a threemonth period), time the beginning teacher spent in mentoring sessions (hours per week), time the mentor 

spent observing the beginning teacher teaching (hours per week), time spent on instruction techniques and 

strategies as part of professional development activities (hours per three-month period), and time spent on 

content area knowledge as part of professional development activities (hours per three-month period). 
xxii 

Executive Summary 

Table 6. Characteristics of District Stayers, Movers, and Leavers by Treatment Status 

(Percentages Except Where Noted) 

Treatment Control Difference 

Teacher Characteristic Stayers Movers Leavers Stayers Movers Leavers Stayers Movers Leavers 

College entrance exam 

scores (SAT combined 

score or equivalent) 1,000 1,009 1,016 1,009 997 1,059 -9 12 -44 

Attended highly 

selective college 29.6 27.6 42.4 27.9 44.8 32.7 1.7 -17.2 9.7 

Major or minor in 

education 73.5 61.8 70.3 74.0 81.8 51.9 -0.5 -20.0 18.4 

Student teaching 

experience (weeks) 14.5 14.5 12.3 13.9 13.6 11.7 0.6 0.8 0.6 

Highest degree is 

master’s or doctorate 20.7 20.5 22.7 21.6 30.5 23.2 -0.9 -10.0 -0.6 

Entered the profession 

through traditional 

four-year program 64.1 61.7 35.7 60.3 62.3 37.6 3.8 -0.6 -1.8 

Certified (regular or 

probationary) 92.1 97.1 95.7 94.2 94.3 87.0 -2.1 2.8 8.7 

Career changer 14.7 10.4 21.1 13.4 15.9 25.8 1.2 -5.5 -4.7 

Unweighted Sample 

Size (Teachers) 394 40 23 361 38 26 

Unweighted Sample 

Size (Schools) 188 34 21 180 36 25 

Source: MPR calculations using data from the College Board and ACT, Inc.; MPR Teacher Background 

Survey administered in 2005-2006, Mobility Survey administered in fall/winter 2006-2007, and 

First and Second Induction Activities Surveys administered in fall/winter 2005-2006 and spring 

2006 to all study teachers. 

Notes: Data are weighted to account for the study design. Sample sizes vary due to item nonresponse. 

The analysis of college entrance exam scores relied on a smaller sample of teachers (190/59/13 

treatment stayers/movers/leavers and 183/44/11 control stayers/movers/leavers) and schools 

(111/36/7 treatment and 106/24/6 control). See Table V.6 for a definition of stayers, movers, and 

leavers. 

None of the differences between treatment stayers and control stayers, between treatment movers and 

control movers, or between treatment leavers and control leavers is significant at the 0.05 level, two-tailed 

test. P-values are suppressed to make the table easier to read. 
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